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Hyperspectral Unmixing

Hyperspectral Unmixing is a procedure that decomposes the measured pixel spectrum of hyperspectral data into a collection of constituent spectral signatures (or endmembers) and a set of corresponding fractional abundances. Hyperspectral Unmixing techniques have been widely used for a variety of applications, such as mineral mapping and land-cover change detection.

Source: An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing

Papers

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Showing 1–50 of 113 papers

TitleStatusHype
Deep Hyperspectral Unmixing using Transformer NetworkCode1
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion ModelCode1
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral UnmixingCode1
Entropic Descent Archetypal Analysis for Blind Hyperspectral UnmixingCode1
Integration of Physics-Based and Data-Driven Models for Hyperspectral Image UnmixingCode1
UnMix-NeRF: Spectral Unmixing Meets Neural Radiance FieldsCode1
Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual LearningCode1
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python PackageCode1
Hyperspectral unmixing with spectral variability using adaptive bundles and double sparsity—0
A Data Dependent Multiscale Model for Hyperspectral Unmixing With Spectral Variability—0
Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation—0
An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing—0
Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation—0
A spatial compositional model (SCM) for linear unmixing and endmember uncertainty estimation—0
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder—0
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing—0
A Low-rank Tensor Regularization Strategy for Hyperspectral Unmixing—0
Hyperspectral Unmixing using Iterative, Sparse and Ensambling Approaches for Large Spectral Libraries Applied to Soils and Minerals—0
Hyperspectral Unmixing via Deep Autoencoder Networks for a Generalized Linear-Mixture/Nonlinear-Fluctuation Model—0
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising—0
Hyperspectral Unmixing Based on Clustered Multitask Networks—0
Deep Learning-Based Correction and Unmixing of Hyperspectral Images for Brain Tumor Surgery—0
Deep Nonlinear Hyperspectral Unmixing Using Multi-task Learning—0
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing—0
Distributed Machine Learning with Sparse Heterogeneous Data—0
DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing—0
A General Framework for Group Sparsity in Hyperspectral Unmixing Using Endmember Bundles—0
A consistent and flexible framework for deep matrix factorizations—0
Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity—0
Transformer based Endmember Fusion with Spatial Context for Hyperspectral Unmixing—0
Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing—0
A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation—0
Enhancing Pure-Pixel Identification Performance via Preconditioning—0
Constrained Nonnegative Matrix Factorization for Blind Hyperspectral Unmixing incorporating Endmember Independence—0
Extracting Optimal Solution Manifolds using Constrained Neural Optimization—0
Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization—0
Fast and Structured Block-Term Tensor Decomposition For Hyperspectral Unmixing—0
GAUSS: Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness—0
Generalized Separable Nonnegative Matrix Factorization—0
HYPERION: Hyperspectral Penetrating-type Ellipsoidal Reconstruction for Terahertz Blind Source Separation—0
Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis—0
Hyperspectral Image Generation with Unmixing Guided Diffusion Model—0
A graph Laplacian regularization for hyperspectral data unmixing—0
A Dual Symmetric Gauss-Seidel Alternating Direction Method of Multipliers for Hyperspectral Sparse Unmixing—0
Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review—0
Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders—0
Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey—0
Hyperspectral Unmixing Network Inspired by Unfolding an Optimization Problem—0
Hyperspectral Unmixing of Agricultural Images taken from UAV Using Adapted U-Net Architecture—0
Adaptive Multi-Order Graph Regularized NMF with Dual Sparsity for Hyperspectral Unmixing—0
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